Methods and systems for image intra-prediction mode management

ABSTRACT

Embodiments of the present invention relate to methods and systems for ordering, communicating and applying pixel intra-prediction modes.

RELATED REFERENCES

This application is a continuation of U.S. patent application Ser. No.10/404,298, entitled, “Methods and Systems for Image Intra-PredictionMode Organization, filed Mar. 31, 2003, now U.S. Pat. No. 7,386,048;which claims the benefit of U.S. Provisional Patent Application No.60/319,272 filed May 28, 2002 and which claims the benefit of U.S.Provisional Patent Application No. 60/319,390, filed Jul. 11, 2002. Allapplications listed in this paragraph are hereby incorporated herein byreference.

BACKGROUND

Embodiments of the present invention relate to intra-prediction for animage.

Digital video requires a large amount of data to represent each andevery frame of a digital video sequence (e.g., series of frames) in anuncompressed manner. It is not feasible for most applications totransmit uncompressed digital video across computer networks because ofbandwidth limitations. In addition, uncompressed digital video requiresa large amount of storage space. The digital video is normally encodedin some manner to reduce the storage requirements and reduce thebandwidth requirements.

One technique for encoding digital video is interframe encoding.Interframe encoding exploits the fact that different frames of videotypically include regions of pixels, normally selected as x by x blocks,that remain substantially the same. During the encoding process a motionvector interrelates the movement of a block of pixels in one frame to ablock of similar pixels in another frame. Accordingly, the system is notrequired to encode the block of pixels twice, but rather encodes theblock of pixels once and provides a motion vector to predict the otherblock of pixels.

Another technique for encoding digital video is intraframe encoding.Intraframe encoding encodes a frame or a portion thereof withoutreference to pixels in other frames.

Typically intraframe encoding encodes the frame, or portions thereof, ona block by block basis. For example, in MEPG-2 the intraframe encodingmakes use of discrete cosine transforms of a block of pixels andsubsequent encoding of the transformed coefficients. Other intraframeencoding techniques exist, such as for example, wavelet encoding.

In general, these techniques employ relatively large data tables forreferencing prediction modes. Memory for these data tables can beburdensomely expensive for many low cost machines. Moreover, it is alsoburdensomely expensive to provide sufficient memory within processingdevices to store the data table. Also, the resulting system hasincreased complexity with the large data table.

BRIEF DESCRIPTION OF THE SEVERAL DRAWINGS

The following drawings depict only typical embodiments of the presentinvention and are not therefore to be considered to be limiting of itsscope, the invention will be described and explained with additionalspecificity and detail through the use of the accompanying drawings inwhich:

FIG. 1 illustrates some forms of block adjacency;

FIG. 2 illustrates a block of pixels and the adjacent pixels forprediction;

FIG. 3 illustrates general prediction mode directions;

FIG. 4 illustrates the general directions of prediction modes in anembodiment of the present invention;

FIG. 5 illustrates the general directions of prediction modes in anembodiment of the present invention;

FIG. 6 illustrates the general directions of prediction modes in anembodiment of the present invention;

FIG. 7 illustrates the general directions of prediction modes in anembodiment of the present invention;

FIG. 8 illustrates the general directions of prediction modes in anembodiment of the present invention;

FIG. 9 is a block diagram illustrating mode estimation in someembodiments of the present invention

FIG. 10 is a block diagram illustrating mode estimation in embodimentswith an ordered set of prediction modes;

FIG. 11 is a block diagram illustrating mode estimation with orderedsets associated with numerical values;

FIG. 12 is a block diagram illustrating mode estimation options whensome adjacent block data is unavailable;

FIG. 13 is a block diagram illustrating mode order modification in someembodiments of the present invention;

FIG. 14 is a block diagram illustrating the methods of an embodiment ofthe present invention in which an estimated mode is used to modify modeorder usage; and

FIG. 15 is a block diagram illustrating the method of an embodiment ofthe present invention in which an estimate mode is used to modify modeorder using specific designators.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

Embodiments of the present invention comprise methods and systemsrelated to intra-prediction of images. As all embodiments are related tointra-prediction, the terms “intra-prediction” and “prediction” may beused interchangeably to refer to intra-prediction processes.

Embodiments of the present invention use intraframe coding orintracoding to exploit spatial redundancies within a video image.Because adjacent blocks generally have similar attributes, theefficiency of the coding process is improved by referencing the spatialcorrelation between adjacent blocks. This correlation may be exploitedby prediction of a target block based on prediction modes used inadjacent blocks.

A digital image may be divided into blocks for more efficient processingor for other reasons. As illustrated in FIG. 1, a target block “C” 12may be situated adjacent to adjacent block “A,” 14 which is locatedimmediately above target block “C” 12. Another adjacent block “B” 16 islocated immediately to the left of target block “C” 12. Other blocksthat share boundaries with target block “C” 12 may also be considered tobe adjacent blocks to block “C” 12.

Blocks may comprise various numbers of pixels in differentconfigurations. For example, a block may comprise a 4×4 array of pixels.A block may also comprise a 16×16 array of pixels or an 8×8 array. Otherpixel configurations, including both square and rectangular arrays mayalso make up a block.

Each pixel in a target block may be predicted with reference to dataregarding pixels in adjacent blocks. This adjacent pixel data oradjacent block data comprises the prediction modes used to predict thoseadjacent blocks or adjacent pixels. Specific adjacent pixels and pixelswithin a target block may be referenced using an alphanumeric index asillustrated in FIG. 2. FIG. 2 illustrates a 4×4 target block, such asblock “C” 12 comprising 16 pixels designated by lower case alphabeticcharacters 22. Pixels in an adjacent block immediately above the targetblock are designated by capital alphabetic characters 24. Pixels in anadjacent block immediately to the left of the target block aredesignated by capital alphabetical characters 26. The bottom right pixel25 in an adjacent block above and to the left of the target block 12 isdesignated by the capital letter “Q”.

Prediction modes may comprise instructions or algorithms for predictingspecific pixels in a target block. These modes may refer to one or moreadjacent block pixels as described in the following mode descriptions.

Prediction Modes

Mode 0: Vertical Prediction

a, e, i, m may be predicted by A

b, f, j, n, may be predicted by B,

c, g, k, o, may be predicted by C

d, j, l, p may be predicted by D

Mode 1: Horizontal Prediction

a, b, c, d, may be predicted by I

e, f, g, h, may be predicted by J

i, j, k, l, may be predicted by K

m, n, o, p, may be predicted by L

Mode 2: DC Prediction

If all samples A, B, C, D, I, J, K, L, are available, all samples may bepredicted by (A+B+C+D+I+J+K+L+4)>>3. If A, B, C, and D are not availableand I, J, K, and L are available, all samples may be predicted by(I+J+K+L+2)>>2. If I, J, K, and L are not available and A, B, C, and Dare available, all samples may be predicted by (A+B+C+D+2)>>2. If alleight samples are not available, the prediction for all luma samples inthe block may be 128. A block may be always predicted in this mode.

Mode 3: diagonal down/left prediction a may be predicted by (A + 2B +C + I + 2J + K + 4) >> 3 b, e may be predicted by (B + 2C + D + J + 2K +L + 4) >> 3 c, f, i may be predicted by (C + 2D + E + K + 2L + M + 4) >>3 d, g, j, m may be predicted by (D + 2E + F + L + 2M + N + 4) >> 3 h,k, n may be predicted by (E + 2F + G + M + 2N + O + 4) >> 3 l, o may bepredicted by (F + 2G + H + N + 2O + P + 4) >> 3 p may be predicted by(G + H + O + P + 2) >> 2

Mode 4: diagonal down/right prediction m may be predicted by (J + 2K +L + 2) >> 2 i, n may be predicted by (I + 2J + K + 2) >> 2 e, j, o maybe predicted by (Q + 2I + J + 2) >> 2 a, f, k, p may be predicted by(A + 2Q + I + 2) >> 2 b, g, l may be predicted by (Q + 2A + B + 2) >> 2c, h may be predicted by (A + 2B + C + 2) >> 2 d may be predicted by(B + 2C + D + 2) >> 2

Mode 5: vertical-left prediction a, j may be predicted by (Q + A + 1) >>1 b, k may be predicted by (A + B + 1) >> 1 c, l may be predicted by(B + C + 1) >> 1 d may be predicted by (C + D + 1) >> 1 e, n may bepredicted by (I + 2Q + A + 2) >> 2 f, o may be predicted by (Q + 2A +B + 2) >> 2 g, p may be predicted by (A + 2B + C + 2) >> 2 h may bepredicted by (B + 2C + D + 2) >> 2 i may be predicted by (Q + 2I + J +2) >> 2 m may be predicted by (I + 2J + K + 2) >> 2

Mode 6: horizontal-down prediction a, g may be predicted by (Q +I + 1) >> 1 b, h may be predicted by (I + 2Q + A + 2) >> 2 c may bepredicted by (Q + 2A + B + 2) >> 2 d may be predicted by (A + 2B + C +2) >> 2 e, k may be predicted by (I + J + 1) >> 1 f, l may be predictedby (Q + 2I + J + 2) >> 2 i, o may be predicted by (J + K + 1) >> 1 j, pmay be predicted by (I + 2J + K + 2) >> 2 m may be predicted by (K +L + 1) >> 1 n may be predicted by (J + 2K + L + 2) >> 2

Mode 7: vertical-right prediction a may be predicted by (2A + 2B + J +2K + L + 4) >> 3 b, i may be predicted by (B + C + 1) >> 1 c, j may bepredicted by (C + D + 1) >> 1 d, k may be predicted by (D + E + 1) >> 1l may be predicted by (E + F + 1) >> 1 e may be predicted by (A + 2B +C + K + 2L + M + 4) >> 3 f, m may be predicted by (B + 2C + D + 2) >> 2g, n may be predicted by (C + 2D + E + 2) >> 2 h, o may be predicted by(D +2E + F + 2) >> 2 p may be predicted by (E + 2F + G + 2) >> 2

Mode 8: horizontal-up prediction a may be predicted by (B + 2C + D +2I + 2J + 4) >> 3 b may be predicted by (C + 2D + E + I + 2J + K + 4) >>3 c, e may be predicted by (J + K + 1) >> 1 d, f may be predicted by(J + 2K + L + 2) >> 2 g, i may be predicted by (K + L + 1) >> 1 h, j maybe predicted by (K + 2L + M + 2) >> 2 l, n may be predicted by (L +2M +N + 2) >> 2 k, m may be predicted by (L + M + 1) >> 1 o may be predictedby (M + N + 1) >> 1 p may be predicted by (M + 2N + O + 2) >> 2

The ordering process, which is based upon the likelihood of producing alesser prediction error for each of the modes, increases the codingefficiently, reduces the memory requirements, and may be at leastpartially mathematically defined.

Each prediction mode may be described by a general direction ofprediction as described verbally in each of the mode titles above (i.e.,horizontal up, vertical and diagonal down left). A prediction mode mayalso be described graphically by an angular direction. This angulardirection may be expressed through a diagram with arrows radiatingoutward from a center point as shown in FIG. 3. In this type of diagram,each arrow and the center point may represent a prediction mode. Theangle corresponding to a prediction mode has a general relationship tothe direction from the weighted average location of the adjacent pixelsused to predict the target pixel to the actual target pixel location.However, the modes are more precisely defined in the definitions aboveand in the JVT standard. In FIG. 3, the center point 32 represents nodirection so this point may be associated with a DC prediction mode. Ahorizontal arrow 34 may represent a horizontal prediction mode. Avertical arrow 36 may represent a vertical prediction mode. An arrowextending from the center point diagonally downward to the right atapproximately a 45 degree angle from horizontal 38 may represent aDiagonal Down/Right (DDR) prediction mode. An arrow extending from thecenter point diagonally downward to the left at approximately a 45degree angle from horizontal 40 may represent a Diagonal Down/Left (DDL)prediction mode. Both the DDR and DDL prediction modes may be referredto as diagonal prediction modes.

An arrow extending from the center point diagonally upward to the rightat approximately a 22.5 degree angle from horizontal 42 may represent aHorizontal Up (HU) prediction mode. An arrow extending from the centerpoint diagonally downward to the right at approximately a 22.5 degreeangle from horizontal 44 may represent a Horizontal Down (HD) predictionmode. An arrow extending from the center point diagonally downward tothe right at approximately a 67.5 degree angle from horizontal 46 mayrepresent a Vertical Right (VR) prediction mode. An arrow extending fromthe center point diagonally downward to the left at approximately a 67.5degree angle from horizontal 48 may represent a Vertical Left (VL)prediction mode. The HU, HD, VR and VL prediction modes may be referredto collectively as intermediate angle prediction modes.

Many other prediction modes may be created and described using thisangular description scheme.

Prediction Mode Order

The present inventors have determined that prediction modes may beordered in a manner generally consistent with their likelihood ofproducing a reduced prediction error. With the prediction modes orderedaccording to their general likelihood of producing a lesser predictionerror, the resulting data itself may have a greater tendency to be moreconsistently ordered. Furthermore, communication of modes may takeadvantage of coding techniques that reduce memory and bandwidthrequirements. For example, the present inventors determined that thehorizontal prediction mode and the vertical prediction mode aregenerally more likely than diagonal prediction modes, which aregenerally more likely than intermediate angle prediction modes. Inaddition, a DC prediction mode (e.g., when an adjacent block is coded ininter mode) is generally less likely than horizontal and verticalprediction modes and generally more likely than diagonal predictionmodes.

For blocks that do not border discontinuities such as image edges orswipe/swath boundaries, the order established in some embodiments of thepresent invention may be expressed, in general terms, as follows:vertical and horizontal prediction modes are more likely to produce areduced prediction error than a DC prediction mode and that a DCprediction mode is more likely to produce a reduced prediction errorthan diagonal prediction modes and that diagonal prediction modes aremore likely to produce a reduced prediction error than intermediateangle prediction modes.

For blocks near edges or boundaries or where adjacent block or pixelprediction mode data is not available, the order established in someembodiments of the present invention may be expressed, in general terms,as follows: DC prediction mode is more likely to produce a reducedprediction error than vertical and horizontal prediction modes andvertical and horizontal prediction modes are more likely to produce areduced prediction error than diagonal prediction modes and thatdiagonal prediction modes are more likely to produce a reducedprediction error than intermediate angle prediction modes.

In a first set of embodiments as illustrated in FIG. 4, modes may bedefined in order as follows:

Mode 0: Vertical prediction

Mode 1: Horizontal prediction

Mode 2: DC prediction

Mode 3: Diagonal Down/Left prediction

Mode 4: Diagonal Down/Right prediction

Mode 5: Horizontal Down prediction

Mode 6: Vertical Right prediction

Mode 7: Vertical Left prediction

Mode 8: Horizontal Up prediction

In a second set of embodiments, as illustrated in FIG. 5, modes may bedefined in order as follows:

Mode 0: Horizontal prediction

Mode 1: Vertical prediction

Mode 2: DC prediction

Mode 3: Diagonal Down/Left prediction

Mode 4: Diagonal Down/Right prediction

Mode 5: Horizontal Down prediction

Mode 6: Vertical Right prediction

Mode 7: Vertical Left prediction

Mode 8: Horizontal Up prediction

In a third set of embodiments, as illustrate in FIG. 6, modes may bedefined in order as follows:

Mode 0: Vertical prediction

Mode 1: Horizontal prediction

Mode 2: DC prediction

Mode 3: Diagonal Down/Left prediction

Mode 4: Diagonal Down/Right prediction

Mode 5: Vertical Right prediction

Mode 6: Horizontal Down prediction

Mode 7: Vertical Left prediction

Mode 8: Horizontal Up prediction

In a fourth set of embodiments, as illustrated in FIG. 7, modes may bedefined in order as follows:

Mode 0: Horizontal prediction

Mode 1: Vertical prediction

Mode 2: DC prediction

Mode 3: Diagonal Down/Left prediction

Mode 4: Diagonal Down/Right prediction

Mode 5: Vertical Right prediction

Mode 6: Horizontal Down prediction

Mode 7: Vertical Left prediction

Mode 8: Horizontal Up prediction

In a fifth set of embodiments, as illustrated in FIG. 8, modes may bedefined in order as follows:

Mode 0: DC prediction

Mode 1: Vertical prediction

Mode 2: Horizontal prediction

Mode 3: Diagonal Down/Left prediction

Mode 4: Diagonal Down/Right prediction

Mode 5: Vertical Right prediction

Mode 6: Horizontal Down prediction

Mode 7: Vertical Left prediction

Mode 8: Horizontal Up prediction

It should be noted that the mode order may vary beyond these exemplaryorders in various other embodiments of the present invention.

In some embodiments of the present invention, the horizontal prediction(mode 0) and the vertical prediction (mode 1) may be reversed, ifdesired. Also, it is to be understood that the diagonal down/leftprediction mode and the horizontal down prediction mode may be reversed,if desired. In addition, it is to be understood the diagonal down/rightprediction (mode 5), the vertical right prediction (mode 6), thevertical left prediction (mode 7), and the horizontal up prediction(mode 8) may be reordered, if desired. Further, it is desirable that theDC prediction is between the mode 0/mode 1 set and the mode 3/mode 4set, but may be located between mode 3/mode 4 set and mode 5/mode 6/mode7/mode 8 set, if desired, or any other location. Moreover, the angledmodes 3-8 may be renumbered as desired without significant impact on theencoding efficiency.

In some embodiments of the present invention, the prediction modes maybe reordered for all of the respective blocks (e.g., those blocks usingthe described prediction scheme) using such a prediction basis. Inaddition, less than all of the respective blocks (e.g., those blocksusing the described prediction scheme) may use such a prediction basis,for example, more than 50%, 75% or 90%, if desired. Also, the order ofthe prediction modes may be the same or varied for different blocks.Further, the reordering of each of the modes of such a prediction basis(e.g., in a predetermined consistent manner) is preferably at least 5modes, 6 modes, or 7 modes, with the remaining being ordered in anyother manner. In addition, the order of the prediction modes ispreferably 0, 1, 2, 3, 4, 5, 6, 7, 8. Other predefined ordering of theprediction modes may likewise be employed.

Some embodiments of the present invention may comprise one or more datatables for organization of mode data. With the modes being generallyarranged in an ordered manner, this may be used together with each cellin a data table, to provide a more ordered set. For example, each entryin the data table may include the ordered set of numbers 0, 1, 2, 3, 4,5, 6, 7, 8, and 9. Alternatively, the ordered set of numbers in the datatable may include 5, 6, 7, 8, or 9 sets of ordered numbers for eachentry in the data table. For example, the data table entries may includethe following sets of data entries {1, 2, 3, 5, 7}; {0, 1, 2, 3, 4, 5,6}; {0, 1, 3, 5, 6, 7, 8}, where each of the numbers in the set are ofincreasing numerical value. Alternatively for example, the data tableentries may include the following sets of data entries {1, 2, 3, 5, 7};{0, 1, 2, 3, 4, 5, 6}; {0, 1, 3, 5, 6, 7, 8}, where each set is includedin at least 25%, or 35%, or 50%, or 75%, or 90%, or more, of the cells.In this manner, the table will have significantly more predictabilitythan known data table methods, which decreases memory requirements.

The predetermined manner of the ordering of the sets of data entriesshould be independent of the prediction modes of adjoining sets ofpixels (e.g. macroblocks). It is to be understood that the data tablemay be “static” in nature or may be effectively dynamically generated,in whole or in part, when needed based upon patterns in the data.Accordingly, a mathematical equation or an algorithm may be used todetermine the entries, which in this case the “table” could be createdby such a technique. Accordingly, a “data table” as used herein is notmerely restricted to a static table, but further includes such a set ofvalues, however determined, that are used for such prediction.

Unfortunately, the substitution of the previous mode numbers with thenew mode numbers (e.g., a substitution of numbers into the cells ofknown data tables), while perhaps an improvement, still results in agenerally unordered set of data.

Estimating a Pixel Prediction Mode Based on Adjacent Block Data

In contrast to the generally unordered set of data shown, even withsubstitutions, the present inventors came to the further realizationthat the most likely prediction mode should be ordered first, the secondmost likely prediction mode ordered second, if desired, followed by theremaining modes in a predetermined manner. The predetermined mannershould be independent of the prediction modes of adjoining macroblocks.The preferred order of the remaining modes should be in a decreasinglikelihood of occurrence of the remaining modes (most likely predictionmode, and if desired, second most likely prediction mode).

Based on the intra prediction modes of block A and block B, as shown inFIG. 1, the intra prediction mode order for block C may be defined asfollows:

(1) If both block A and block B are “outside” (e.g., not available),only DC prediction (mode 2) is permitted, therefore the intra predictionmode order for block C is {2}.

(2) If block A is “outside” (e.g., not available) and block B is not“outside”, only DC prediction (mode 2) and horizontal prediction (mode0) are permitted for block C, therefore;

(i) if block B is 2, intra prediction mode order for block C is {2, 0};

(ii) otherwise, intra prediction mode order for block C is {0, 21}.

(3) If block A is not “outside” but block B is “outside”, only DCprediction (mode 2) and vertical prediction (mode 1) are permitted forblock C, therefore

(i) if block A is 2, intra prediction mode order for block C is {2, 1};

(ii) otherwise, intra prediction mode order for block C is {1, 2}.

(4) If neither block A nor block B is “outside”,

(i) if the prediction mode of block A is less than the prediction modeof block B, then intra prediction mode order for block C is {intraprediction block mode A, intra prediction block mode B, other modes inascending order};

(ii) if the prediction mode of block A is greater than the predictionmode of block B, then intra prediction mode order for block C is {intraprediction block mode B, intra prediction block mode A, other modes inascending order};

(iii) if the prediction mode of block A equals the prediction mode ofblock B, then intra prediction mode order for block C is {intraprediction block mode A, other modes in ascending order}.

For example, if the prediction mode of block A is 3 and the predictionmode of block B is 1, then intra prediction mode order for block C is{1, 3, 0, 2, 4, 5, 6, 7, 8}. With the modes arranged in a generallydecreasing likelihood (or increasing) of occurrence, then the automaticarrangement of the remaining modes of occurrence will still be generallyarranged in the proper sequence. The ordering of the sequence fromhigher to lower probability increases the likelihood of the properprediction toward the front. With entropy encoding this decreases theresulting encoded bit stream. Other arrangements may likewise be used.

Conceptually the aforementioned selection scheme is based upon theprinciple that if the prediction of block A is X and the prediction ofblock B is Y, then it is likely the prediction of block C is X or Y. Theprediction for X and/or Y is located at the start of the list and theremaining modes are sequentially listed thereafter.

Stated another way, when the prediction modes of A and B are known(including the case that A or B or both are outside the slice) the mostprobable mode of C is given, namely, the minimum of the modes used forblocks A and B. If one of the blocks A or B is “outside” the mostprobable mode is equal to prediction mode 2. The ordering of predictionmodes assigned to blocks C is therefore the most probable mode followedby the remaining modes in the ascending order.

Embodiments of the present invention may be described with reference toFIG. 9. In these embodiments, a target block is selected 50 forprediction. A prediction mode used for prediction of a first adjacentblock, which is immediately adjacent to said target block, is thendetermined 52. A prediction mode used for prediction of a secondadjacent block, which is also adjacent to said target block is alsodetermined 54. These adjacent block prediction modes are then examined56 to determine which is more likely to produce a lesser predictionerror.

In other embodiments of the present invention, as illustrated in FIG.10, a set of prediction modes is ordered 58 according to the modes'likelihood of producing a lesser prediction error. A target block isselected 60. The prediction mode used for a first adjacent block isdetermined 62 and the prediction mode used for a second adjacent blockis also determined 64. These two prediction modes are then examined 66to determine which occurs first in the ordered set of modes therebycorresponding to the mode with the higher likelihood of producing alesser prediction error.

In further embodiments of the present invention, as illustrated in FIG.11, a set of prediction modes is ordered 68 by likelihood of producing alesser prediction error. These modes in the ordered set are thenassociated 70 with numerical values such that modes with a higherlikelihood of producing a lesser prediction error are associated withlower numerical values. The mode used to predict a first adjacent blockis then determined 72 and the mode used to predict a second adjacentblock is also determined 74. These adjacent block modes are thenexamined to determine which mode is associated with a lower numericalvalue. This mode is designated as the estimated mode for prediction ofthe target block 76.

In still further embodiments, as illustrated in FIG. 12, a set ofprediction modes is ordered 78 by likelihood of producing a lesserprediction error. These modes in the ordered set are then associated 80with numerical values such that modes with a higher likelihood ofproducing a lesser prediction error are associated with lower numericalvalues. An attempt 82 is made to determine the mode used to predict afirst adjacent block and an attempt 84 is made to determine the modeused to predict a second adjacent block. If the prediction mode used topredict the first adjacent block is not available 86, a defaultprediction mode, such as a DC prediction mode, may be designated 90 asan estimated prediction mode for the target block. Also, if theprediction mode used to predict the second adjacent block is notavailable 88, a default prediction mode, such as a DC prediction mode,may be designated 90 as an estimated prediction mode for the targetblock. When the adjacent block prediction modes are available, theseadjacent block modes may be examined to determine which mode isassociated with a lower numerical value. This mode is then designated 92as the estimated mode for prediction of the target block.

Modification of Prediction Mode Order Based on Adjacent Block Data

In some embodiments of the present invention the prediction mode ordersdescribed above, which have been determined independently of theadjacent block data, may be modified with adjacent block data.Prediction mode estimates determined with reference to adjacent blockdata can be inserted into prediction mode orders to modify the orders toreflect the additional information obtained from adjacent block data.

In some of these embodiments, a prediction mode estimate, based onadjacent block data, can be inserted directly into a prediction modeorder set. Typically, the prediction mode estimate will be inserted orprepended at the front of the prediction mode order at the position ofthe mode most likely to produce a reduced prediction error. However, insome embodiments the estimate may be inserted at different positions inthe mode order.

In some embodiments of the present invention, as shown in FIG. 13, aprediction mode order is selected 102 wherein the prediction mode orderelements may be arranged according to their likelihood of producing alesser prediction error. In other words, the first element in the orderrepresents the prediction mode most likely to yield a lesser predictionerror, the next element in the order represents the prediction mode thatis the next most likely to yield a lesser prediction error and so on tothe last element in the order, which represents the prediction mode inthe order that is least likely to yield a lesser prediction error.

A prediction mode estimate is also determined 104, as described above.This estimate is determined using adjacent block data. Generally, theestimate is the prediction mode used in one or more adjacent blocks thatis likely to yield a lesser prediction error. However, the estimate maybe determined in other ways. When sufficient adjacent block predictionmode data is not available, such as at an image edge or a sliceboundary, a prediction mode for the target block may be estimated basedon the lack of one or more adjacent blocks or their prediction modedata. In many cases, a DC prediction mode will be estimated whenadjacent block data is limited or unavailable.

In some embodiments, once the estimated prediction mode is estimated,the estimated prediction mode may be placed 106 into the mode order asthe mode most likely to yield a lesser prediction error. In someembodiments, this will be the first mode in the order or the modeassociated with the lowest numerical value.

In other embodiments, the estimated prediction mode may take precedenceover the pre-selected mode order. In some of these embodiments, asillustrated in FIG. 14, a pre-selected mode order is designated 110 atthe encoder and the decoder. This order comprises a set of predictionmodes arranged in order of likelihood of yielding a lesser predictionerror or some other order. An estimated prediction mode is alsodetermined 112 based on adjacent block data. This estimated predictionmode is determined at the encoder and the decoder according to the samealgorithm or method. The encoder also determines the actual bestprediction mode 114 for predicting a pixel based on motion vectors orother known techniques. The encoder may, then, compare 116 the actualbest prediction mode to the estimated prediction mode to determinewhether they are the same. If the estimated prediction mode is the samemode as the actual best prediction mode, the encoder may signal to thedecoder that the estimated prediction mode is to be used 118. In someembodiments, this estimated prediction mode signal may be performed witha 1-bit flag to signify whether the estimated mode is to be used on not.

If the estimated prediction mode is not the actual best prediction mode,the encoder may signal to the decoder that another mode may be used 120.This may be performed by reference to the pre-established mode order.The encoder may determine which mode in the mode order is mostequivalent to the actual best prediction mode and signal the decoder touse that mode.

When an ordered set of prediction modes is used, the set order may berearranged once further data is obtained. For example, an ordered set ofprediction modes may be re-ordered when an estimated prediction mode isdetermined or when a best actual prediction mode is determined. In thesecases, the modifying mode may be interjected into the ordered set,placed ahead of the ordered set or, in some cases, removed from theordered set.

In some embodiments of the present invention, each mode in the modeorder may be associated with a numerical value according to the order.In these embodiments, the numerical value associated with the mode to beused may be sent to the decoder to signal the decoder to use thatprediction mode. In some of these embodiments, as illustrated in FIG.15, a mode order comprising 9 prediction modes may be selected 130. Anestimated prediction mode based on adjacent block data, and which is oneof the 9 modes in the order, may also be determined 132. A bestprediction mode may also be determined 134 by motion vector methods orother methods. The best prediction mode may then be compared to theestimated prediction mode 136. If the estimated prediction mode issubstantially the same as the best prediction mode, the decoder may besignaled with a 1-bit designator to use the estimated prediction mode,which is already identified at the decoder 138. If the estimatedprediction mode is not equivalent to the best prediction mode, theestimated prediction mode is essentially eliminated from the mode order140. This elimination may be performed by re-ordering the set, skippingthe estimated mode in the order or by other means. The remaining orderwill effectively comprise 8 modes, which can be represented by a 3-bitdesignator. This 3-bit designator may be sent to the decoder 142 todesignate which mode to use for prediction.

The terms and expressions employed in the foregoing specification areused therein as terms of description and not of limitation, and there isno intention in the use of such terms and expressions of excludingequivalents of the features shown and described or portions thereof, itbeing recognized that the scope of the invention is defined and limitedonly by the claims that follow.

1. A method for communicating a spatial pixel prediction mode for atarget block in an image, said method comprising a. storing an orderedset of pixel prediction modes, wherein said prediction modes are orderedin order of decreasing probability of producing a lesser predictionerror and wherein said order is not based on characteristics of saidimage; b. determining a first adjacent mode actually used for predictinga first adjacent block, which is adjacent to a target block, whereinsaid first adjacent mode is selected based on an actual prediction errorand said first adjacent mode is in said ordered set; c. determining asecond adjacent mode actually used for predicting a second adjacentblock, which is adjacent to said target block, wherein said secondadjacent mode is selected based on an actual prediction error and saidsecond adjacent mode is in said ordered set; d. selecting one of saidfirst adjacent mode and said second adjacent mode as an estimated modefor said target block, wherein said selecting is based on the order ofsaid ordered set; e. determining an actual prediction mode for saidtarget block by determining which mode in said ordered set results inthe least prediction error; f. sending a first signal indicating to usesaid estimated mode to predict said target block when said actualprediction mode is substantially similar to said estimated mode; g.eliminating said estimated mode from said ordered set thereby creating areduced ordered set when said actual prediction mode is notsubstantially similar to said estimated mode; and h. sending a secondsignal indicating which prediction mode to use when said first signalindicates not to use said estimated mode.
 2. A method as described inclaim 1 wherein at least a portion of the modes in said ordered set arein an order as follows: i. one mode taken from an axis subset consistingof a horizontal prediction mode and a vertical prediction mode; j. theother mode of said axis subset; and k. a DC prediction mode.
 3. A methodfor communicating a pixel prediction mode for a target block in animage, said method comprising: l. storing an ordered set of pixelprediction modes, wherein said order is not based on characteristics ofsaid image; m. determining a first adjacent mode actually used forpredicting a first adjacent block, which is adjacent to a target block,wherein said first adjacent mode is selected based on an actualprediction error and said first adjacent mode is in said ordered set; n.determining a second adjacent mode actually used for predicting a secondadjacent block, which is adjacent to said target block, wherein saidsecond adjacent mode is selected based on an actual prediction error andsaid second adjacent mode is in said ordered set; o. selecting one ofsaid first adjacent mode and said second adjacent mode as an estimatedmode for said target block, wherein said selecting is based on therelative positions of said adjacent modes in said ordered set; p.modifying said ordered set by moving said estimated mode from itsoriginal position in said ordered set to a new position in said orderedset thereby creating a modified ordered set.
 4. A method as described inclaim 3 further comprising: q. determining an actual prediction mode forsaid target block by determining which mode in said ordered set resultsin the least prediction error; and r. sending a prediction mode signalindicating which mode in said modified ordered set corresponds to saidactual prediction mode.
 5. A method for determining a pixel predictionmode for a target block in an image, said determining occurring at adecoder, said method comprising: s. storing an ordered set of pixelprediction modes, wherein said order is not based on characteristics ofsaid image; t. determining a first adjacent mode actually used forpredicting a first adjacent block, which is adjacent to a target block,wherein said first adjacent mode is in said ordered set; u. determininga second adjacent mode actually used for predicting a second adjacentblock, which is adjacent to said target block, wherein said secondadjacent mode is in said ordered set; v. selecting one of said firstadjacent mode and said second adjacent mode as an estimated mode forsaid target block, wherein said selecting is based on said ordered set;w. using said estimated mode as a prediction mode in decoding saidtarget block when a first signal indicates to use said estimated mode;x. eliminating said estimated mode from said ordered set therebycreating a reduced ordered set when said first signal indicates not touse said estimated mode; and y. using a prediction mode in said reducedordered set, said prediction mode being indicated by a second signal,when said first signal indicates not to use said estimated mode.